Open AccessMultimodal Provenance-based Analysis of Collaboration in Business Processes
Author(s) -
Maria Luiza Falci,
Andréa Fernandes Magalhães,
Aline Paes,
Vanessa Braganholo,
Daniel de Oliveira
Publication year - 2021
Publication title -
journal of information and data management
Language(s) - English
Resource type - Journals
ISSN - 2178-7107
DOI - 10.5753/jidm.2021.1923
Subject(s) - computer science , provenance , process (computing) , set (abstract data type) , business process , data science , information retrieval , engineering , work in process , petrology , operations management , programming language , geology , operating system
Modeling business processes as a set of activities to accomplish goals naturally makes them be executed several times. Usually, such executions produce a large portion of provenance data in different formats such as text, audio, and video. Such a multiple-type nature gives origin to multimodal provenance data. Analyzing multimodal provenance data in an integrated form may be complex and error-prone when manually performed as it requires extracting information from free-text, audio, and video files. However, such an analysis may generate valuable insights into the business process. The present article presents MINERVA (Multimodal busINEss pRoVenance Analysis). This approach focuses on identifying improvements that can be implemented in business processes, as well as in collaboration analysis using multimodal provenance data. MINERVA was evaluated through a feasibility study that used data from a consulting company.